According to the National Highway Traffic Safety Administration, car accident statistics in the US show that a large percentage of fatal crashes are caused by a driver's inability to make a correct split-second judgment while driving. This problem is even more serious for elderly drivers or those with disabilities, such as poor hearing, poor vision or poor reflexes. One of the goals of this research is to help these people drive safely, without giving up their own independence but also without endangering themselves or others.
Past research in the field of intelligent vehicles has been mostly related to:                adaptive cruise control,        collision-avoidance in the front and rear,        lane departure warnings,        parallel-parking assistance,        blind spot monitoring, and        autonomous vehicles (self-driven cars).        
The majority of these systems rely on the presence of visible lane markers on the road, which are detected by using computer vision systems, GPS systems or digital maps for knowledge of the road's geometry, or ultrasonic sensors for sensing presence of obstacles in the front and rear of the car within a very short range. Heavy dependence on maps can sometimes make these systems vulnerable to unexpected objects on the streets, including fallen debris, road-blocks, children at play, cyclists, or cars that are broken down or stranded.
Another sensing modality uses short-range radar or LIDAR (Light Detection and Ranging) systems, which have been tested by scientists in various research labs to sense traffic up to a range of 200 meters. Some researchers have also suggested the use of Time-of-Flight cameras or 3D sensors such as MICROSOFT's XBOX KINECT, which uses infrared (IR) sensing. However, KINECT is quite deficient when used in open sunlight or outdoors with moving objects and surroundings. In addition, time-of-flight cameras have also not been shown to achieve the level of accuracy desired.
Many current projects are under development to provide drivers with assistance. Among these, lane-change-assist is an appealing idea to most drivers, because this is where they are most likely to make mistakes even when they are fully awake and driving in good road conditions. But this is a complex problem since it not only requires knowledge of the movement of cars in the next lane (including the blind zone) but also cars in the lane after that, any of which may suddenly decide to merge into the next lane with no warnings. It also requires knowledge of the approximate speed and acceleration of these cars, to avoid colliding with one which may approach at a high speed or decide to accelerate or decelerate to avoid other traffic.
Thus, improvements in driver assistance systems are desired.